Question 1

Speed up Firestore data access in a simple, cost-effective way

❌ Move the data to Spanner
❌ Move the data to BigQuery
🟩 Cache the data using Memorystore
❌ Move the data to Bigtable

Explanation:

Firestore already performs well for operational workloads.
To increase speed without migrating, use Memorystore (Redis) as a cache — the most cost-effective improvement.

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Question 2

Where to store combined analytics data (Oracle + GA + logs) for easy querying and low cost?

❌ Spanner
🟩 BigQuery
❌ Firestore
❌ Cloud SQL

Explanation:

BigQuery is designed for:

• large datasets

• analytics

• SQL queries

• low storage cost

Perfect solution for business intelligence and trend analysis.

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Question 3

Global financial company → low latency worldwide + strong consistency

❌ Firestore
🟩 Spanner
❌ BigQuery
❌ Cloud SQL

Explanation:

Spanner is the only Google Cloud database that delivers:

• global horizontal scale

• strong consistency

• <100ms worldwide reads/writes

It’s ideal for global fintech.

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Question 4

Simple, cost-effective managed storage for user prefs + products + reviews (small dataset)

❌ Spanner
🟩 Firestore
❌ BigQuery
❌ Cloud SQL

Explanation:

Firestore is:

• serverless

• inexpensive

• highly available

• perfect for small/medium JSON-style data

• ideal for web/mobile applications

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🧾 Summary Table

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